{"id":4870,"date":"2026-08-29T23:49:36","date_gmt":"2026-08-29T18:19:36","guid":{"rendered":"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/"},"modified":"2026-08-29T23:49:36","modified_gmt":"2026-08-29T18:19:36","slug":"kubernetes-cluster-guide-architecture-and-best-practices","status":"publish","type":"post","link":"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/","title":{"rendered":"Kubernetes Cluster Guide: Architecture and Best Practices"},"content":{"rendered":"<p>Timestamp: 03:14 UTC. The pager went off because the API server decided it didn&#8217;t feel like responding to heartbeats anymore.<\/p>\n<pre class=\"codehilite\"><code class=\"language-bash\">$ kubectl get nodes\nError from server (Timeout): the server was unable to return a response in the time allotted, but may still be processing the request (get nodes)\n\n$ kubectl get pods -A\nUnable to connect to the server: dial tcp 10.0.0.1:6443: i\/o timeout\n<\/code><\/pre>\n<p>I stared at the terminal, the blue light of the monitor searing my retinas while the rest of the house slept. This is the reality of the modern &#8220;kubernetes cluster&#8221;. We were told it would be self-healing. We were promised that the &#8220;reconciliation loop&#8221; would be our mechanical savior, a tireless deity that would ensure our desired state always matched our actual state. <\/p>\n<p>Instead, I\u2019m looking at a dead control plane and a Slack channel full of automated alerts from Prometheus that are essentially screaming &#8220;Everything is on fire and I don&#8217;t know why.&#8221;<\/p>\n<p>The culprit, as it turns out, wasn&#8217;t a massive traffic spike or a sophisticated DDoS attack. It was a single, misconfigured <code>PodDisruptionBudget<\/code> (PDB) combined with a minor version upgrade on a managed node group in a v1.28.x environment. We tried to drain a node. The scheduler tried to move a pod. The PDB said &#8220;No.&#8221; The automation tried again. And again. And again. Eventually, the <code>kube-controller-manager<\/code> got stuck in a logic loop that bloated the <code>etcd<\/code> transaction log until the disk I\/O on the master nodes hit 100% utilization. <\/p>\n<p>Welcome to the future of infrastructure. It\u2019s just a thousand shell scripts in a trench coat, pretending to be an operating system.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_80 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a93e1781d99a\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a93e1781d99a\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#The_Etcd_Ghost_in_the_Machine\" >The Etcd Ghost in the Machine<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#The_Networking_Layer_of_Lies_CNI_and_the_Iptables_Nightmare\" >The Networking Layer of Lies (CNI and the Iptables Nightmare)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#The_Scheduler_An_Over-Confident_Matchmaker\" >The Scheduler: An Over-Confident Matchmaker<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#The_Kubelet_and_the_Cgroup_v2_Migration_Trap\" >The Kubelet and the Cgroup v2 Migration Trap<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#The_Hidden_Cost_of_Managed_%E2%80%9CKubernetes_Cluster%E2%80%9D_Services\" >The Hidden Cost of Managed &#8220;Kubernetes Cluster&#8221; Services<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#The_Reconciliation_Loop_as_a_DoS_Vector\" >The Reconciliation Loop as a DoS Vector<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#Hard-Won_Lessons_from_the_Trenches\" >Hard-Won Lessons from the Trenches<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/#Related_Articles\" >Related Articles<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"The_Etcd_Ghost_in_the_Machine\"><\/span>The Etcd Ghost in the Machine<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>When people talk about a &#8220;kubernetes cluster&#8221;, they usually focus on the shiny parts\u2014the YAML, the containers, the &#8220;serverless&#8221; abstractions. They rarely talk about the brittle, temperamental heart of the beast: <code>etcd<\/code>. <\/p>\n<p>In this specific incident, our <code>etcd<\/code> quorum collapsed because of a latency spike that would have been a rounding error in any other system. But in a &#8220;kubernetes cluster&#8221;, <code>etcd<\/code> is the only source of truth. If the disk takes 15ms instead of 5ms to commit a proposal, the whole house of cards starts to wobble.<\/p>\n<pre class=\"codehilite\"><code class=\"language-bash\"># journalctl -u etcd -f\nMar 14 03:16:22 ip-10-0-42-12 etcd[2104]: store.index: error: failed to get key &quot;\/registry\/events\/default\/log-processor-7f8d9b.17c2a...&quot;\nMar 14 03:16:23 ip-10-0-42-12 etcd[2104]: raft: 8e9234c21a... is starting a new election at term 42\nMar 14 03:16:24 ip-10-0-42-12 etcd[2104]: raft: 8e9234c21a... failed to send message to 9f21... (exceeded max message size)\n<\/code><\/pre>\n<p>The &#8220;max message size&#8221; error is the kiss of death. It means your cluster state has become so bloated with event metadata\u2014mostly garbage generated by failing health checks\u2014that the nodes can no longer synchronize. We\u2019ve built a system where the diagnostic data about the failure is the very thing that prevents the system from recovering. <\/p>\n<p>The &#8220;kubernetes cluster&#8221; architecture relies on a consensus algorithm (Raft) that is notoriously sensitive to network jitter. We run these things on virtualized hardware, with virtualized networking, on top of &#8220;bursty&#8221; SSDs, and then we act surprised when the consensus breaks. I spent two hours manually compacting the <code>etcd<\/code> keyspace using <code>etcdctl<\/code> just to get the API server to stop timing out. This isn&#8217;t &#8220;cloud-native&#8221; engineering; it&#8217;s digital archaeology, digging through layers of compacted JSON to find the one record that&#8217;s stalling the entire pipeline.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Networking_Layer_of_Lies_CNI_and_the_Iptables_Nightmare\"><\/span>The Networking Layer of Lies (CNI and the Iptables Nightmare)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Once I got the control plane back, I realized the &#8220;kubernetes cluster&#8221; was still a ghost town. The pods were &#8220;Running,&#8221; but they couldn&#8217;t talk to each other. <\/p>\n<p>This brings us to the CNI (Container Network Interface). In our case, we\u2019re running a standard VPC-CNI on AWS, which is supposed to be &#8220;robust.&#8221; What they don&#8217;t tell you is that every time a node joins or leaves the &#8220;kubernetes cluster&#8221;, the CNI has to perform a frantic dance of attaching ENIs (Elastic Network Interfaces), assigning secondary IP addresses, and updating the local <code>iptables<\/code> or <code>ipvs<\/code> rules.<\/p>\n<p>If you\u2019ve never looked at the <code>iptables<\/code> output on a production node with 200+ services, don&#8217;t. It\u2019s a horror story. Thousands of lines of rules, chains, and jumps that the <code>kube-proxy<\/code> has to manage. <\/p>\n<pre class=\"codehilite\"><code class=\"language-bash\"># iptables -L -t nat | wc -l\n14282\n<\/code><\/pre>\n<p>Fourteen thousand rules. Every packet that enters that node has to traverse a significant portion of that list just to find out which local socket it belongs to. We\u2019ve replaced a simple router with a massive, distributed, eventually-consistent lookup table that breaks if the <code>kube-proxy<\/code> pod restarts too quickly. <\/p>\n<p>In this incident, the CNI had entered a &#8220;race condition&#8221; where it thought it had assigned an IP address to a new pod, but the underlying VPC hadn&#8217;t finished plumbing the route. The pod started, the <code>readinessProbe<\/code> failed because the network wasn&#8217;t there, the <code>kubelet<\/code> killed the pod, and the cycle started over. Each cycle left a &#8220;zombie&#8221; <code>veth<\/code> pair on the host. By 04:00 AM, the node had run out of available network interfaces, not because we were out of capacity, but because the &#8220;kubernetes cluster&#8221; was too fast for its own underlying infrastructure.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Scheduler_An_Over-Confident_Matchmaker\"><\/span>The Scheduler: An Over-Confident Matchmaker<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The &#8220;kubernetes cluster&#8221; scheduler is a piece of software that thinks it\u2019s much smarter than it actually is. It looks at CPU and Memory &#8220;requests&#8221; as if they are hard facts, rather than the wild guesses made by developers who haven&#8217;t looked at a resource graph in six months.<\/p>\n<p>During the recovery, I watched the scheduler try to bin-pack our heaviest Java microservices onto a single worker node because that node happened to have the most &#8220;available&#8221; memory. It didn&#8217;t account for the fact that these services are all I\/O intensive and would immediately starve the <code>kubelet<\/code> of disk cycles.<\/p>\n<p>Here is the manifest that nearly killed us. A developer, in their infinite wisdom, had applied this <code>PodDisruptionBudget<\/code>:<\/p>\n<pre class=\"codehilite\"><code class=\"language-yaml\">apiVersion: policy\/v1\nkind: PodDisruptionBudget\nmetadata:\n  name: critical-app-pdb\nspec:\n  minAvailable: 1\n  selector:\n    matchLabels:\n      app: critical-app\n<\/code><\/pre>\n<p>On the surface, it looks fine. &#8220;Keep at least one pod alive.&#8221; But the <code>critical-app<\/code> only had one replica. When the node it was on needed to go down for a security patch, the &#8220;kubernetes cluster&#8221; entered a deadlock. The <code>NodeDrainer<\/code> couldn&#8217;t remove the pod because it would violate the PDB. The <code>AutoScaler<\/code> couldn&#8217;t kill the node because it wasn&#8217;t empty. The <code>UpgradeController<\/code> just kept retrying the drain every 10 seconds, flooding the API server with requests.<\/p>\n<p>This is the &#8220;magic&#8221; of automation. It\u2019s a system that will happily spend $5,000 in compute time trying to move a single 100MB container because a YAML file told it to, without ever stopping to ask a human, &#8220;Hey, this isn&#8217;t working, should I stop?&#8221;<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Kubelet_and_the_Cgroup_v2_Migration_Trap\"><\/span>The Kubelet and the Cgroup v2 Migration Trap<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>We recently moved the &#8220;kubernetes cluster&#8221; to nodes running v1.28 on an Amazon Linux 2023 base, which defaults to <code>cgroup v2<\/code>. You\u2019d think this would be a &#8220;seamless&#8221; transition (to use a word I despise). It wasn&#8217;t.<\/p>\n<p>The way <code>kubelet<\/code> interacts with the Linux kernel\u2019s resource accounting changed. Suddenly, our &#8220;OOMKilled&#8221; (Out of Memory) events weren&#8217;t just killing the container; they were occasionally causing the entire <code>containerd<\/code> runtime to hang because of how the memory pressure was being reported up the chain.<\/p>\n<p>I spent thirty minutes at 04:30 AM looking at <code>dmesg<\/code> logs on a worker node, trying to figure out why a Python script was able to lock up the entire node&#8217;s container runtime.<\/p>\n<pre class=\"codehilite\"><code class=\"language-text\">[ 1420.4821] oom-kill:constraint=CONSTRAINT_MEMCG,nodemask=(null),cpuset=kubepods-besteffort-pod...\n[ 1420.4822] Memory cgroup out of memory: Killed process 12904 (python3) total-vm:1048576kB, anon-rss:512000kB, file-rss:0kB, shmem-rss:0kB\n[ 1420.5100] containerd-shim[12800]: segfault at 0 ip 000055...\n<\/code><\/pre>\n<p>The &#8220;kubernetes cluster&#8221; is supposed to isolate these failures. That\u2019s the whole point of containers. But the abstraction is leaky. The kernel doesn&#8217;t care about your &#8220;Namespace&#8221; or your &#8220;ResourceQuota&#8221; when it\u2019s starving for pages. It will kill whatever it needs to kill to stay alive, and often, the first victim is the very agent (<code>kubelet<\/code>) that is supposed to be managing the mess.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Hidden_Cost_of_Managed_%E2%80%9CKubernetes_Cluster%E2%80%9D_Services\"><\/span>The Hidden Cost of Managed &#8220;Kubernetes Cluster&#8221; Services<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>We use a managed service because we thought it would mean fewer 3:00 AM pages. That was a lie. Managed services just move the &#8220;black box&#8221; further away from you. <\/p>\n<p>When the API server went down, I couldn&#8217;t check the logs. I had to wait for the cloud provider&#8217;s &#8220;Control Plane Logging&#8221; to eventually ingest the data into a separate log-aggregation service, which has a 5-minute ingestion delay. When you\u2019re in the middle of a cascading failure, 5 minutes is an eternity. <\/p>\n<p>The &#8220;kubernetes cluster&#8221; managed by a provider often hides the <code>etcd<\/code> metrics. You don&#8217;t see the disk latency until it&#8217;s already triggered a leader election. You don&#8217;t see the CPU throttling on the API server until the <code>kubectl<\/code> commands start failing. We are paying a premium for the privilege of being blindfolded during an emergency.<\/p>\n<p>And let\u2019s talk about the &#8220;Add-ons.&#8221; The VPC-CNI, the CoreDNS autoscaler, the storage drivers. These are all just more pods running in your &#8220;kubernetes cluster&#8221;, often with &#8220;PriorityClass: system-cluster-critical&#8221;. If one of these &#8220;managed&#8221; components has a bug\u2014like the time a CoreDNS update caused a circular dependency in DNS resolution\u2014it can take down your entire application stack, and you have no way to roll it back because the managed service &#8220;owns&#8221; that configuration.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Reconciliation_Loop_as_a_DoS_Vector\"><\/span>The Reconciliation Loop as a DoS Vector<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The core philosophy of a &#8220;kubernetes cluster&#8221; is the reconciliation loop.<br \/>\n1. Observe state.<br \/>\n2. Compare to desired state.<br \/>\n3. Act to fix the difference.<\/p>\n<p>This sounds great in a textbook. In practice, it\u2019s a Distributed Denial of Service attack waiting to happen. When our cluster started failing, every single controller in the system\u2014the <code>DeploymentController<\/code>, the <code>ReplicaSetController<\/code>, the <code>EndpointSliceController<\/code>\u2014all noticed the failure at the same time. <\/p>\n<p>They all started hammering the API server with &#8220;Update&#8221; and &#8220;Patch&#8221; requests. The API server, already struggling with <code>etcd<\/code> latency, started queueing these requests. The <code>kube-apiserver<\/code> has a &#8220;Priority and Fairness&#8221; (APF) configuration, but in v1.29, if you haven&#8217;t tuned those &#8220;FlowSchemas&#8221; perfectly, the system will prioritize &#8220;system&#8221; traffic so heavily that you, the administrator, can&#8217;t even get a <code>get nodes<\/code> request through to see what\u2019s happening.<\/p>\n<p>We\u2019ve built a system that prioritizes its own internal bureaucracy over the actual work it\u2019s supposed to be doing. The &#8220;kubernetes cluster&#8221; was so busy telling itself that it was broken that it didn&#8217;t have any resources left to actually fix itself.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Hard-Won_Lessons_from_the_Trenches\"><\/span>Hard-Won Lessons from the Trenches<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>It\u2019s 05:45 AM now. The &#8220;kubernetes cluster&#8221; is stable, mostly because I manually deleted half the failing pods and scaled the deployments to zero to give the API server room to breathe. My coffee is cold, and I have a meeting in three hours to explain why &#8220;the cloud&#8221; failed. <\/p>\n<p>If you\u2019re going to run a &#8220;kubernetes cluster&#8221; and you want to sleep, here is the survival guide.<\/p>\n<p><strong>1. Your PDBs are a Suicide Note.<\/strong><br \/>\nNever, ever set <code>minAvailable<\/code> to equal your total replica count. If you have 2 replicas, <code>minAvailable<\/code> should be 1. If you have 1 replica, don&#8217;t use a PDB at all. The &#8220;kubernetes cluster&#8221; will respect your PDB until it kills the entire node group. It is a suicide pact, not a safety net.<\/p>\n<p><strong>2. Etcd is Not a Database; It\u2019s a Bomb.<\/strong><br \/>\nMonitor your <code>etcd_disk_wal_fsync_duration_seconds<\/code> and <code>etcd_network_peer_round_trip_time_seconds<\/code> like your life depends on it, because it does. If those numbers trend upward, your &#8220;kubernetes cluster&#8221; is about to have a heart attack. Use the fastest NVMe drives you can find for <code>etcd<\/code> storage. Do not use &#8220;General Purpose&#8221; cloud storage.<\/p>\n<p><strong>3. Resource Limits are Lies.<\/strong><br \/>\nA <code>limits: memory: 1Gi<\/code> doesn&#8217;t mean your app gets 1Gi. It means the kernel will kill your app the millisecond it touches 1.00001Gi. Always set your <code>requests<\/code> equal to your <code>limits<\/code> to avoid the &#8220;Burstable&#8221; QoS class. &#8220;Burstable&#8221; is just another word for &#8220;The scheduler will over-provision this node and then the OOMKiller will pick a random victim when things get tight.&#8221;<\/p>\n<p><strong>4. The CNI is the Weakest Link.<\/strong><br \/>\nThe networking in a &#8220;kubernetes cluster&#8221; is a fragile overlay. If you are using AWS, increase the <code>WARM_IP_TARGET<\/code> in your VPC-CNI settings so you always have a buffer of IPs. If you\u2019re using Calico or Flannel, watch your MTU settings. A 20-byte mismatch in MTU will result in &#8220;random&#8221; connection resets that will haunt your dreams and are nearly impossible to debug with standard tools.<\/p>\n<p><strong>5. Trust No Automation.<\/strong><br \/>\nThe &#8220;Operator Pattern&#8221; is just a way to move manual mistakes into code. Every &#8220;Operator&#8221; you add to your &#8220;kubernetes cluster&#8221;\u2014whether it\u2019s for Prometheus, Postgres, or Certificates\u2014is another reconciliation loop that can go rogue. We had an &#8220;Auto-healing&#8221; operator that once deleted 40 nodes because it misinterpreted a temporary network partition as a total hardware failure.<\/p>\n<p><strong>6. Keep the Control Plane Lean.<\/strong><br \/>\nStop putting everything in the &#8220;kubernetes cluster&#8221;. If you can run it on a managed database service or a simple VM, do it. The more you cram into the cluster, the more complex the dependency graph becomes. When the &#8220;kubernetes cluster&#8221; fails, you want your database and your logging to be <em>outside<\/em> the blast radius.<\/p>\n<p><strong>7. Learn the Low-Level Tools.<\/strong><br \/>\nWhen the API server is down, <code>kubectl<\/code> is useless. You need to know how to use <code>crictl<\/code> to inspect containers directly on the node. You need to know how to read <code>journalctl<\/code> logs. You need to understand <code>iptables-save<\/code>. If you only know the &#8220;kubernetes cluster&#8221; through the lens of the API, you are not an SRE; you are a passenger.<\/p>\n<p>The &#8220;kubernetes cluster&#8221; is a marvel of engineering, but it is also a monument to our own hubris. We took the simple problem of &#8220;running a program on a computer&#8221; and added ten layers of abstraction, three layers of virtualized networking, and a distributed consensus algorithm. We got &#8220;scalability,&#8221; sure. But we traded our sleep for it.<\/p>\n<p>I\u2019m going to bed. If the pager goes off again, I\u2019m quitting and becoming a carpenter. Wood doesn&#8217;t have reconciliation loops. Wood doesn&#8217;t have a CNI. Wood just sits there. And right now, that sounds like heaven.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Related_Articles\"><\/span>Related Articles<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Explore more insights and best practices:<\/p>\n<ul>\n<li><a href=\"https:\/\/itsupportwale.com\/blog\/top-cybersecurity-jobs-in-2024-careers-salary-and-skills\/\">Top Cybersecurity Jobs In 2024 Careers Salary And Skills<\/a><\/li>\n<li><a href=\"https:\/\/itsupportwale.com\/blog\/docker-best-practices-optimize-and-secure-your-containers\/\">Docker Best Practices Optimize And Secure Your Containers<\/a><\/li>\n<li><a href=\"https:\/\/itsupportwale.com\/blog\/what-is-a-docker-container-a-complete-guide-for-beginners\/\">What Is A Docker Container A Complete Guide For Beginners<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Timestamp: 03:14 UTC. The pager went off because the API server decided it didn&#8217;t feel like responding to heartbeats anymore. $ kubectl get nodes Error from server (Timeout): the server was unable to return a response in the time allotted, but may still be processing the request (get nodes) $ kubectl get pods -A Unable &#8230; <a title=\"Kubernetes Cluster Guide: Architecture and Best Practices\" class=\"read-more\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/\" aria-label=\"Read more  on Kubernetes Cluster Guide: Architecture and Best Practices\">Read more<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4870","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Kubernetes Cluster Guide: Architecture and Best Practices - ITSupportWale<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/itsupportwale.com\/blog\/kubernetes-cluster-guide-architecture-and-best-practices\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kubernetes Cluster Guide: Architecture and Best Practices - ITSupportWale\" \/>\n<meta property=\"og:description\" content=\"Timestamp: 03:14 UTC. The pager went off because the API server decided it didn&#8217;t feel like responding to heartbeats anymore. $ kubectl get nodes Error from server (Timeout): the server was unable to return a response in the time allotted, but may still be processing the request (get nodes) $ kubectl get pods -A Unable ... 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